Principal Engineer, AI & Emerging Technology

CPP Investments | Investissements RPC•Toronto, ON

3d•Onsite

About The Position

As a Principal Engineer for AI & Emerging Tech, you will lead the design, development, and deployment of scalable AI solutions and products that support CPP Investments’ enterprise-wide goals. This role combines deep technical expertise with strategic leadership, requiring strong collaboration with cross-functional stakeholders, guidance of technical teams, and a forward-looking mindset to evaluate and integrate emerging technologies. You will play a key role in ensuring technical excellence, responsible AI adoption, and operational readiness of GenAI solutions—spanning experimentation, piloting, and full-scale deployment.

Requirements

University degree in Computer Science, Engineering, or a related discipline; advanced degrees and relevant certifications are considered an asset.
Minimum of 10 years of progressive software engineering experience, including experience leading the design and delivery of enterprise-scale technology solutions.
Demonstrated experience leading AI, GenAI, or emerging technology initiatives, including driving solutions from concept through production deployment.
Proven ability to influence and lead cross-functional teams in a collaborative, fast-paced, and matrixed environment.
Strong experience designing, building, and operating enterprise-grade AI solutions with a focus on scalability, reliability, security, governance, and operational excellence.
Deep expertise developing production-ready AI applications leveraging frontier large language models (LLMs), including OpenAI, Anthropic, and Google models, as well as advanced prompt engineering techniques such as chain-of-thought and few-shot learning.
Experience architecting and implementing agentic AI systems using technologies and patterns such as Model Context Protocol (MCP), GraphRAG, and multi-agent orchestration frameworks.
Hands-on experience with modern GenAI development frameworks, including LangChain, LlamaIndex, and Amazon Bedrock.
Strong software engineering fundamentals with experience building distributed systems, RESTful services, event-driven architectures, APIs, and data-intensive applications.
Experience developing cloud-native solutions on AWS, including EKS, Fargate, Lambda, Athena, Glue, and Lake Formation.
Proficiency with Infrastructure as Code and containerization technologies, including Terraform, Puppet, Docker, and Kubernetes.
Experience building modern web applications using technologies such as Next.js, React, and TypeScript.
Strong Python development experience, including data engineering and ETL orchestration using Apache Airflow, DAGs, NumPy, Pandas, and Boto3.
Experience implementing automated testing and evaluation frameworks, including Ragas, Playwright, Selenium, and related quality assurance practices.
Strong understanding of software development lifecycle (SDLC) practices, DevSecOps principles, Agile methodologies, and delivery tools such as JIRA, Confluence, and JIRA Align.
Knowledge of LLM fine-tuning techniques, model evaluation, and AI performance optimization approaches.
Experience working with business intelligence and analytics platforms such as QuickSight and Tableau.
Strategic thinker with the ability to translate business objectives into technology strategy and execution plans.
Strong leadership and influencing skills, with the ability to build alignment across technical and business stakeholders.
Exceptional problem-solving and analytical capabilities, with a focus on delivering practical and scalable solutions.
Effective communicator with strong verbal, written, and presentation skills, capable of engaging audiences at all levels of the organization.
Demonstrated ability to navigate ambiguity, drive innovation, and adapt to rapidly evolving technologies and business priorities.
Collaborative and inclusive team player with a commitment to mentoring, knowledge sharing, and fostering engineering excellence.
Results-oriented with a strong sense of ownership, accountability, and continuous improvement.

Nice To Haves

Knowledge of financial markets, investment management, or capital markets technology is considered a strong asset.

Responsibilities

Lead end-to-end technical architecture, planning and execution of complex AI solutions, pilots and projects.
Produce high-level solution architectures aligned with emerging technologies, enterprise capabilities and business outcomes.
Drive strategic technical decisions to ensure scalability, performance, and security of AI models and systems.
Mentor and develop engineers, fostering best practices in software and AI development.
Improve engineering maturity by introducing shared patterns, practices, and reusable components.
Champion responsible AI practices by addressing bias, fairness, explainability, and regulatory compliance.
Conduct risk assessments and implement mitigation strategies throughout solution lifecycles.
Evaluate and integrate emerging technologies including AI/ frameworks, retrieval augmentation, and cloud-native deployments.
Lead technical communications with senior stakeholders and ensure transparency in decision-making.
Actively participate in project reviews, identifying improvement opportunities in architecture, delivery, and process.
Align technical initiatives with broader organizational goals through collaboration with Data Science, Cybersecurity, Product, and Operations teams.